• DocumentCode
    2355862
  • Title

    High-throughput computation of pairwise sequence similarities for multiple genome comparisons using ScalaBLAST

  • Author

    Shah, Anuj R. ; Markowitz, Victor M. ; Oehmen, Christopher S.

  • Author_Institution
    Pacific Northwest Nat. Lab., Richland
  • fYear
    2007
  • fDate
    8-9 Nov. 2007
  • Firstpage
    89
  • Lastpage
    91
  • Abstract
    Genome sequence comparisons of exponentially growing data sets form the foundation for the comparative analysis tools provided by community biological data resources such as the integrated microbial genome (IMG) system at the joint genome institute (JGI). For a genome sequencing center to provide multiple-genome comparison capabilities, it must keep pace with exponentially growing collection of sequence data, both from its own genomes, and from public genomes. We present an example of how ScalaBLAST, a high-throughput sequence analysis program, harnesses increasingly critical high-performance computing to perform sequence analysis, enabling, for example, all vs. all BLAST runs across 2 million protein sequences within a day using thousands of processors as opposed to conventional comparison methods that would take years to complete.
  • Keywords
    biology computing; genetics; molecular biophysics; molecular configurations; proteins; ScalaBLAST; genome sequencing; high-throughput sequence analysis program; multiple genome comparisons; pairwise sequence similarities; protein sequences; Bioinformatics; Biology computing; Computational biology; Data analysis; Genomics; Performance analysis; Proteins; Resource management; Sequences; Technology management;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Life Science Systems and Applications Workshop, 2007. LISA 2007. IEEE/NIH
  • Conference_Location
    Bethesda, MD
  • Print_ISBN
    978-1-4244-1813-8
  • Electronic_ISBN
    978-1-4244-1813-8
  • Type

    conf

  • DOI
    10.1109/LSSA.2007.4400891
  • Filename
    4400891